Java Code Examples for org.nd4j.linalg.factory.Nd4j#copy()

The following examples show how to use org.nd4j.linalg.factory.Nd4j#copy() . You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may check out the related API usage on the sidebar.

Example 1

Source File: DeepGL.java From ml-models with Apache License 2.0

6 votes

private void diffuse(List<Pruning.Feature> featuresList) {
    INDArray ndDiffused = Nd4j.create(embedding.shape());
    Nd4j.copy(embedding, ndDiffused);

    featuresList.addAll(featuresList);
    features = featuresList.toArray(new Pruning.Feature[0]);

    for (int i = features.length / 2; i < features.length; i++) {
        features[i] = new Pruning.Feature("diffuse", features[i]);
    }

    for (int diffIteration = 0; diffIteration < diffusionIterations; diffIteration++) {
        INDArray ndDiffusedTemp = Nd4j.create(embedding.shape());
        nodeQueue.set(0);
        final ArrayList<Future<?>> futures = new ArrayList<>();
        for (int i = 0; i < concurrency; i++) {
            futures.add(executorService.submit(new DiffusionTask(ndDiffused, ndDiffusedTemp)));
        }
        ParallelUtil.awaitTermination(futures);
        ndDiffused = ndDiffusedTemp;
    }
    embedding = Nd4j.concat(1, embedding, ndDiffused);
}

Example 2

Source File: PruningTest.java From ml-models with Apache License 2.0

6 votes

@Test
public void testGetCols() {

    INDArray origEmbedding = Nd4j.create(new double[][]{
            {0.00, 1.00, 0.00},
            {0.00, 0.00, 1.00},
            {0.00, 1.00, 1.00},
            {0.00, 2.00, 2.00},
            {1.00, 0.00, 0.00},
            {1.00, 0.00, 0.00},
            {2.00, 0.00, 0.00},
    });

    int[] featIdsToKeep = {2, 1, 0};

    INDArray ndPrunedEmbedding = Nd4j.create(origEmbedding.shape());
    Nd4j.copy(origEmbedding, ndPrunedEmbedding);
    INDArray columns = ndPrunedEmbedding.getColumns(featIdsToKeep);
    System.out.println("columns = \n" + columns);
}

Example 3

Source File: Gan4Exemple.java From dl4j-tutorials with MIT License

6 votes

private static void discCp2GenParam() {
    Map<String, INDArray> paramTableGen = genNet.paramTable();

    //恢复数据
    Set<String> genKeySet = paramTableGen.keySet();
    for (Iterator<String> iter = genKeySet.iterator(); iter.hasNext();) {
        String key = iter.next();
        String[] keys = key.split("_");
        Integer keyIdx = Integer.parseInt(keys[0]);
        if (keyIdx >= startIdx) {
            String discKey = (keyIdx - startIdx) + "_" + keys[1];
            INDArray item = discNet.getParam(discKey);
            Nd4j.copy(item, genNet.getParam(key));
        }
    }
}

Example 4

Source File: CudaExecutionerTest.java From nd4j with Apache License 2.0

6 votes

@Test
public void testSoftmax1D_1() throws Exception {
    INDArray input1T = Nd4j.create(new double[]{ -0.75, 0.58, 0.42, 1.03, -0.61, 0.19, -0.37, -0.40, -1.42, -0.04});
    INDArray input1 = Nd4j.create(new double[]{ -0.75, 0.58, 0.42, 1.03, -0.61, 0.19, -0.37, -0.40, -1.42, -0.04});
    INDArray input2 = Nd4j.zerosLike(input1);
    Nd4j.copy(input1, input2);
    INDArray output1 = Nd4j.create(1, 10);
    INDArray output1T = Nd4j.create(1, 10);

    System.out.println("FA --------------------");
    Nd4j.getExecutioner().exec(new OldSoftMax(input1, output1));
    Nd4j.getExecutioner().exec(new OldSoftMax(input1T, output1T));
    System.out.println("FB --------------------");

    System.out.println("Softmax = " + output1);
    INDArray output2 = Nd4j.create(1,10);
    Nd4j.getExecutioner().exec(new SoftMaxDerivative(input2, output2));
    System.out.println("Softmax Derivative = " + output2);

    INDArray assertion1 = Nd4j.create(new double[]{0.04, 0.16, 0.14, 0.26, 0.05, 0.11, 0.06, 0.06, 0.02, 0.09});

    assertArrayEquals(assertion1.data().asFloat(), output1.data().asFloat(), 0.01f);
    assertArrayEquals(assertion1.data().asFloat(), output1T.data().asFloat(), 0.01f);

}

Example 5

Source File: CudaTransformsTests.java From nd4j with Apache License 2.0

6 votes

@Test
public void testSoftmax1D_1() throws Exception {
    INDArray input1T = Nd4j.create(new double[]{ -0.75, 0.58, 0.42, 1.03, -0.61, 0.19, -0.37, -0.40, -1.42, -0.04}).transpose();
    INDArray input1 = Nd4j.create(new double[]{ -0.75, 0.58, 0.42, 1.03, -0.61, 0.19, -0.37, -0.40, -1.42, -0.04});
    INDArray input2 = Nd4j.zerosLike(input1);
    Nd4j.copy(input1, input2);
    INDArray output1 = Nd4j.create(1, 10);
    INDArray output1T = Nd4j.create(1, 10);

    System.out.println("FA --------------------");
    Nd4j.getExecutioner().exec(new OldSoftMax(input1, output1));
    Nd4j.getExecutioner().exec(new OldSoftMax(input1T, output1T));
    System.out.println("FB --------------------");

    System.out.println("Softmax = " + output1);
    INDArray output2 = Nd4j.create(1,10);
    Nd4j.getExecutioner().exec(new SoftMaxDerivative(input2, output2));
    System.out.println("Softmax Derivative = " + output2);

    INDArray assertion1 = Nd4j.create(new double[]{0.04, 0.16, 0.14, 0.26, 0.05, 0.11, 0.06, 0.06, 0.02, 0.09});

    assertArrayEquals(assertion1.data().asFloat(), output1.data().asFloat(), 0.01f);
    assertArrayEquals(assertion1.data().asFloat(), output1T.data().asFloat(), 0.01f);

}

Example 6

Source File: NativeOpExecutionerTest.java From nd4j with Apache License 2.0

6 votes

@Test
public void testSoftmax1D_1() throws Exception {
    INDArray input1T = Nd4j.create(new double[]{ -0.75, 0.58, 0.42, 1.03, -0.61, 0.19, -0.37, -0.40, -1.42, -0.04});
    INDArray input1 = Nd4j.create(new double[]{ -0.75, 0.58, 0.42, 1.03, -0.61, 0.19, -0.37, -0.40, -1.42, -0.04});
    INDArray input2 = Nd4j.zerosLike(input1);
    Nd4j.copy(input1, input2);
    INDArray output1 = Nd4j.create(1, 10);
    INDArray output1T = Nd4j.create(1, 10);

    System.out.println("FA --------------------");
    Nd4j.getExecutioner().exec(new OldSoftMax(input1, output1));
    Nd4j.getExecutioner().exec(new OldSoftMax(input1T, output1T));
    System.out.println("FB --------------------");

    System.out.println("Softmax = " + output1);
    INDArray output2 = Nd4j.create(1,10);
    Nd4j.getExecutioner().exec(new SoftMaxDerivative(input2, output2));
    System.out.println("Softmax Derivative = " + output2);

    INDArray assertion1 = Nd4j.create(new double[]{0.04, 0.16, 0.14, 0.26, 0.05, 0.11, 0.06, 0.06, 0.02, 0.09});

    assertArrayEquals(assertion1.data().asFloat(), output1.data().asFloat(), 0.01f);
    assertArrayEquals(assertion1.data().asFloat(), output1T.data().asFloat(), 0.01f);

}

Example 7

Source File: LapackTest.java From nd4j with Apache License 2.0

6 votes

@Test
public void testQRSquare() {
    INDArray A = Nd4j.create(new double[] {1, 2, 3, 4, 5, 6, 7, 8, 9});
    A = A.reshape('c', 3, 3);
    INDArray O = Nd4j.create(A.shape());
    Nd4j.copy(A, O);
    INDArray R = Nd4j.create(A.columns(), A.columns());

    Nd4j.getBlasWrapper().lapack().geqrf(A, R);

    A.mmuli(R);
    O.subi(A);
    DataBuffer db = O.data();
    for (int i = 0; i < db.length(); i++) {
        assertEquals(0, db.getFloat(i), 1e-5);
    }
}

Example 8

Source File: LapackTest.java From nd4j with Apache License 2.0

6 votes

@Test
public void testQRRect() {
    INDArray A = Nd4j.create(new double[] {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12});
    A = A.reshape('f', 4, 3);
    INDArray O = Nd4j.create(A.shape());
    Nd4j.copy(A, O);

    INDArray R = Nd4j.create(A.columns(), A.columns());
    Nd4j.getBlasWrapper().lapack().geqrf(A, R);

    A.mmuli(R);
    O.subi(A);
    DataBuffer db = O.data();
    for (int i = 0; i < db.length(); i++) {
        assertEquals(0, db.getFloat(i), 1e-5);
    }
}

Example 9

Source File: LapackTest.java From nd4j with Apache License 2.0

6 votes

@Test
public void testCholeskyL() {
    INDArray A = Nd4j.create(new double[] {2, -1, 1, -1, 2, -1, 1, -1, 2,});
    A = A.reshape('c', 3, 3);
    INDArray O = Nd4j.create(A.shape());
    Nd4j.copy(A, O);

    Nd4j.getBlasWrapper().lapack().potrf(A, true);

    A.mmuli(A.transpose());
    O.subi(A);
    DataBuffer db = O.data();
    for (int i = 0; i < db.length(); i++) {
        assertEquals(0, db.getFloat(i), 1e-5);
    }
}

Example 10

Source File: LapackTest.java From deeplearning4j with Apache License 2.0

6 votes

@Test
public void testQRSquare() {
    INDArray A = Nd4j.create(new double[] {1, 2, 3, 4, 5, 6, 7, 8, 9});
    A = A.reshape('c', 3, 3);
    INDArray O = Nd4j.create(A.dataType(), A.shape());
    Nd4j.copy(A, O);
    INDArray R = Nd4j.create(A.dataType(), A.columns(), A.columns());

    Nd4j.getBlasWrapper().lapack().geqrf(A, R);

    A.mmuli(R);
    O.subi(A);
    DataBuffer db = O.data();
    for (int i = 0; i < db.length(); i++) {
        assertEquals(0, db.getFloat(i), 1e-5);
    }
}

Example 11

Source File: LapackTest.java From deeplearning4j with Apache License 2.0

6 votes

@Test
public void testQRRect() {
    INDArray A = Nd4j.create(new double[] {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12});
    A = A.reshape('f', 4, 3);
    INDArray O = Nd4j.create(A.dataType(), A.shape());
    Nd4j.copy(A, O);

    INDArray R = Nd4j.create(A.dataType(), A.columns(), A.columns());
    Nd4j.getBlasWrapper().lapack().geqrf(A, R);

    A.mmuli(R);
    O.subi(A);
    DataBuffer db = O.data();
    for (int i = 0; i < db.length(); i++) {
        assertEquals(0, db.getFloat(i), 1e-5);
    }
}

Example 12

Source File: LapackTest.java From deeplearning4j with Apache License 2.0

6 votes

@Test
public void testCholeskyL() {
    INDArray A = Nd4j.create(new double[] {2, -1, 1, -1, 2, -1, 1, -1, 2,});
    A = A.reshape('c', 3, 3);
    INDArray O = Nd4j.create(A.dataType(), A.shape());
    Nd4j.copy(A, O);

    Nd4j.getBlasWrapper().lapack().potrf(A, true);

    A.mmuli(A.transpose());
    O.subi(A);
    DataBuffer db = O.data();
    for (int i = 0; i < db.length(); i++) {
        assertEquals(0, db.getFloat(i), 1e-5);
    }
}

Example 13

Source File: CudaTransformsTests.java From nd4j with Apache License 2.0

5 votes

@Test
public void testSoftmax2D_T() {
    INDArray input1 = Nd4j.create(1000).transpose();
    INDArray input2 = Nd4j.zerosLike(input1);
    Nd4j.copy(input1, input2);
    INDArray output1 = Nd4j.create(1, 1000);
    Nd4j.getExecutioner().exec(new OldSoftMax(input1, output1));
    System.out.println("Softmax = " + output1);
    INDArray output2 = Nd4j.create(1,1000);
    Nd4j.getExecutioner().exec(new SoftMaxDerivative(input2, output2));
    System.out.println("Softmax Derivative = " + output2);

    assertEquals(1.0f, output1.sumNumber().floatValue(), 0.01f);
    assertEquals(1.0f, output2.sumNumber().floatValue(), 0.01f);
}

Example 14

Source File: LapackTest.java From nd4j with Apache License 2.0

5 votes

@Test
public void testCholeskyU() {
    INDArray A = Nd4j.create(new double[] {2, -1, 2, -1, 2, -1, 2, -1, 2,});
    A = A.reshape('f', 3, 3);
    INDArray O = Nd4j.create(A.shape());
    Nd4j.copy(A, O);

    Nd4j.getBlasWrapper().lapack().potrf(A, false);
    A = A.transpose().mmul(A);
    O.subi(A);
    DataBuffer db = O.data();
    for (int i = 0; i < db.length(); i++) {
        assertEquals(0, db.getFloat(i), 1e-5);
    }
}

Example 15

Source File: LapackTest.java From deeplearning4j with Apache License 2.0

5 votes

@Test
public void testCholeskyU() {
    INDArray A = Nd4j.create(new double[] {3, -1, 2, -1, 3, -1, 2, -1, 3,});
    A = A.reshape('f', 3, 3);
    INDArray O = Nd4j.create(A.dataType(), A.shape());
    Nd4j.copy(A, O);

    Nd4j.getBlasWrapper().lapack().potrf(A, false);
    A = A.transpose().mmul(A);
    O.subi(A);
    DataBuffer db = O.data();
    for (int i = 0; i < db.length(); i++) {
        assertEquals(0, db.getFloat(i), 1e-5);
    }
}

Example 16

Source File: Pruning.java From ml-models with Apache License 2.0

4 votes

private INDArray pruneEmbedding(INDArray origEmbedding, int... featIdsToKeep) {
    INDArray ndPrunedEmbedding = Nd4j.create(origEmbedding.shape());
    Nd4j.copy(origEmbedding, ndPrunedEmbedding);
    return ndPrunedEmbedding.getColumns(featIdsToKeep);
}